Hi:
I am trying to estimate the following Markov Switching model of regime heteroskedastic:
inflation in time t = trend inflation + U2S1,t + U3S2,t + U4S1,t S2,t + (h0 + h1S2,t)Nt
where trend inflation = trend inflation(1) + (Q0 + Q1S1,t)Et
Here, Si,t = unobserved state variable that represents the regime shift. Both S1,t and S2,t are assumed to evolve according to 2 independent firstorder twostate Markov chains.
Shocks to the permanent (transitory) component take on the value Q0 (h0) if they are in a lowvolatility state and Q0+Q1 (h0+h1) otherwise.
My question is this: how do you include the state variables into the equation to be estimated? How do you define the state variables (S1,t=0 given S1,t1=0, etc) so that they can be included as regressors? Should the trend inflation equation be included as probability regressors?
Any guidance will be greatly appreciated
Markov switching regimes
Moderators: EViews Gareth, EViews Moderator

 EViews Developer
 Posts: 2642
 Joined: Wed Oct 15, 2008 9:17 am
Re: Markov switching regimes
Two things.
First, it's a little hard to read the notation so I may be misunderstanding what you are trying to do. If so, apologies in advance.
Second, if I am understanding correctly, you have a specification that is bilinear in the states, with the product of the two state variables entering into the observables equation. Note that this doesn't follow the standard form of the linear state space model and cannot be estimated using our tools.
As to the specific question, you simply define new state variables using the @state keyword, and then enter those variables into the observables equation. The manual has examples. Also, you can use the Proc for specifying a state space model to autocreate a specification with some of those characteristics. This can give you an idea of how to adapt these tools to your specification.
Good luck.
First, it's a little hard to read the notation so I may be misunderstanding what you are trying to do. If so, apologies in advance.
Second, if I am understanding correctly, you have a specification that is bilinear in the states, with the product of the two state variables entering into the observables equation. Note that this doesn't follow the standard form of the linear state space model and cannot be estimated using our tools.
As to the specific question, you simply define new state variables using the @state keyword, and then enter those variables into the observables equation. The manual has examples. Also, you can use the Proc for specifying a state space model to autocreate a specification with some of those characteristics. This can give you an idea of how to adapt these tools to your specification.
Good luck.
Re: Markov switching regimes
Thank you Glenn, this is very helpful and much appreciated
Who is online
Users browsing this forum: No registered users and 15 guests